Docker Setup

I have setup the docker container to run the model evaluation.

Initial Query

I have a list of several thousand file paths in /tmp/files. Write a python script that merges the content int 16 files called /tmp/merged_%d for i in 0..15 where each is approximately the same size. "/tmp/files" is a list of file paths, one per line.

LLM Generation

Query

I have a list of several thousand file paths in /tmp/files. Write a python script that merges the content int 16 files called /tmp/merged_%d for i in 0..15 where each is approximately the same size. "/tmp/files" is a list of file paths, one per line.

Output

To achieve the task of merging the content of several thousand file paths listed in `/tmp/files` into 16 approximately equally sized files named `/tmp/merged_%d` (for `i` in 0..15), you can follow the steps outlined in this Python script: 1. Read the file paths from `/tmp/files`. 2. Calculate the total size of all files to determine the approximate size each of the 16 files should be. 3. Iterate through the file paths, reading their content and writing it to one of the 16 output files in a way that balances the total size across these files. Here is a script that does this: 

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import os

def read_file_paths(file_path):
    with open(file_path, 'r') as file:
        return [line.strip() for line in file.readlines()]

def calculate_file_sizes(file_paths):
    return [os.path.getsize(path) for path in file_paths]

def distribute_to_merged_files(file_paths, file_sizes, target_files):
    total_size = sum(file_sizes)
    target_size_per_file = total_size // len(target_files)
    
    current_file_index = 0
    current_file_size = 0
    
    for file_path, file_size in zip(file_paths, file_sizes):
        if current_file_size + file_size > target_size_per_file and current_file_index < len(target_files) - 1:
            # Move to the next file if the current one has reached its target size
            current_file_index += 1
            current_file_size = 0
        
        with open(file_path, 'r') as input_file:
            content = input_file.read()
        
        with open(target_files[current_file_index], 'a') as output_file:
            output_file.write(content)
        
        current_file_size += file_size

def main():
    file_paths = read_file_paths('/tmp/files')
    file_sizes = calculate_file_sizes(file_paths)
    
    target_files = [f'/tmp/merged_{i}' for i in range(16)]
    
    # Ensuring target files are empty before starting
    for target_file in target_files:
        open(target_file, 'w').close()
    
    distribute_to_merged_files(file_paths, file_sizes, target_files)

if __name__ == "__main__":
    main()
This script assumes that all files listed in `/tmp/files` are readable text files and that the system has enough resources to handle the files' content as it reads and writes. Note, however, that this script does not guarantee a perfectly equal distribution of file sizes across the 16 output files but aims to approximate it. Depending on the distribution of the input file sizes, some variation in output file sizes is to be expected.

Extract Code

I extracted the following code from that output: 

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import os

def read_file_paths(file_path):
    with open(file_path, 'r') as file:
        return [line.strip() for line in file.readlines()]

def calculate_file_sizes(file_paths):
    return [os.path.getsize(path) for path in file_paths]

def distribute_to_merged_files(file_paths, file_sizes, target_files):
    total_size = sum(file_sizes)
    target_size_per_file = total_size // len(target_files)
    
    current_file_index = 0
    current_file_size = 0
    
    for file_path, file_size in zip(file_paths, file_sizes):
        if current_file_size + file_size > target_size_per_file and current_file_index < len(target_files) - 1:
            # Move to the next file if the current one has reached its target size
            current_file_index += 1
            current_file_size = 0
        
        with open(file_path, 'r') as input_file:
            content = input_file.read()
        
        with open(target_files[current_file_index], 'a') as output_file:
            output_file.write(content)
        
        current_file_size += file_size

def main():
    file_paths = read_file_paths('/tmp/files')
    file_sizes = calculate_file_sizes(file_paths)
    
    target_files = [f'/tmp/merged_{i}' for i in range(16)]
    
    # Ensuring target files are empty before starting
    for target_file in target_files:
        open(target_file, 'w').close()
    
    distribute_to_merged_files(file_paths, file_sizes, target_files)

if __name__ == "__main__":
    main()

Run Code Interpreter

Running the following program: 

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import os

def read_file_paths(file_path):
    with open(file_path, 'r') as file:
        return [line.strip() for line in file.readlines()]

def calculate_file_sizes(file_paths):
    return [os.path.getsize(path) for path in file_paths]

def distribute_to_merged_files(file_paths, file_sizes, target_files):
    total_size = sum(file_sizes)
    target_size_per_file = total_size // len(target_files)
    
    current_file_index = 0
    current_file_size = 0
    
    for file_path, file_size in zip(file_paths, file_sizes):
        if current_file_size + file_size > target_size_per_file and current_file_index < len(target_files) - 1:
            # Move to the next file if the current one has reached its target size
            current_file_index += 1
            current_file_size = 0
        
        with open(file_path, 'r') as input_file:
            content = input_file.read()
        
        with open(target_files[current_file_index], 'a') as output_file:
            output_file.write(content)
        
        current_file_size += file_size

def main():
    file_paths = read_file_paths('/tmp/files')
    file_sizes = calculate_file_sizes(file_paths)
    
    target_files = [f'/tmp/merged_{i}' for i in range(16)]
    
    # Ensuring target files are empty before starting
    for target_file in target_files:
        open(target_file, 'w').close()
    
    distribute_to_merged_files(file_paths, file_sizes, target_files)

if __name__ == "__main__":
    main()
And got the output:

PyFunc

final: False Resulting in output: False

Docker Setup

I have setup the docker container to run the model evaluation.

Initial Query

I have a list of several thousand file paths in /tmp/files. Write a python script that merges the content int 16 files called /tmp/merged_%d for i in 0..15 where each is approximately the same size. "/tmp/files" is a list of file paths, one per line.

LLM Generation

Query

I have a list of several thousand file paths in /tmp/files. Write a python script that merges the content int 16 files called /tmp/merged_%d for i in 0..15 where each is approximately the same size. "/tmp/files" is a list of file paths, one per line.

Output

To achieve the task of merging several thousand files into 16 approximately equally sized files, you can follow the approach outlined below. This script involves reading the list of file paths from `/tmp/files`, calculating the total size to aim for equal distribution, and then merging the content into 16 files named `/tmp/merged_%d` where `%d` is in the range from 0 to 15. Note: This solution assumes that the size of the content of these files can fit into memory reasonably well. If the files are very large, you might need to adjust the approach to handle memory more efficiently. 

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import os

def get_file_size(file_path):
    """Get the size of a file."""
    return os.path.getsize(file_path)

def merge_files(target_dir, file_paths, num_files=16):
    """Merge files into a specified number of files with approximately equal size."""
    # Calculate total size of all files
    total_size = sum(get_file_size(path) for path in file_paths)
    
    # Target size per merged file
    target_size = total_size // num_files
    
    # Initialize variables
    current_file_size = 0
    current_file_index = 0
    merged_file = None
    
    for file_path in file_paths:
        # If there's no open file or the current file size exceeds the target, switch to a new file
        if not merged_file or current_file_size >= target_size:
            if merged_file:
                merged_file.close()
            merged_file_path = os.path.join(target_dir, f'merged_{current_file_index}')
            merged_file = open(merged_file_path, 'w')
            current_file_index += 1
            current_file_size = 0
        
        with open(file_path, 'r') as f:
            content = f.read()
            merged_file.write(content)
            current_file_size += len(content)
    
    # Close the last merged file
    if merged_file:
        merged_file.close()

def main():
    target_dir = '/tmp'
    file_list_path = '/tmp/files'
    
    # Read the list of file paths
    with open(file_list_path, 'r') as file_list:
        file_paths = [line.strip() for line in file_list.readlines()]
    
    # Sort file paths by size (optional, could help with distribution)
    file_paths.sort(key=get_file_size)
    
    # Merge files
    merge_files(target_dir, file_paths)

if __name__ == '__main__':
    main()
This script opens each file listed in `/tmp/files`, reads its content, and writes it into one of the 16 target files in `/tmp`. It aims to keep the size of these merged files approximately equal by distributing the content based on the total size. Note that this approach does not guarantee perfectly equal file sizes due to the division and the nature of file contents, but it should be reasonably balanced. Remember to have appropriate permissions to read the files listed in `/tmp/files` and write to the `/tmp` directory. Also, consider error handling for cases such as unreadable files or permission issues, which is not extensively covered in this straightforward example.

Extract Code

I extracted the following code from that output: 

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import os

def get_file_size(file_path):
    """Get the size of a file."""
    return os.path.getsize(file_path)

def merge_files(target_dir, file_paths, num_files=16):
    """Merge files into a specified number of files with approximately equal size."""
    # Calculate total size of all files
    total_size = sum(get_file_size(path) for path in file_paths)
    
    # Target size per merged file
    target_size = total_size // num_files
    
    # Initialize variables
    current_file_size = 0
    current_file_index = 0
    merged_file = None
    
    for file_path in file_paths:
        # If there's no open file or the current file size exceeds the target, switch to a new file
        if not merged_file or current_file_size >= target_size:
            if merged_file:
                merged_file.close()
            merged_file_path = os.path.join(target_dir, f'merged_{current_file_index}')
            merged_file = open(merged_file_path, 'w')
            current_file_index += 1
            current_file_size = 0
        
        with open(file_path, 'r') as f:
            content = f.read()
            merged_file.write(content)
            current_file_size += len(content)
    
    # Close the last merged file
    if merged_file:
        merged_file.close()

def main():
    target_dir = '/tmp'
    file_list_path = '/tmp/files'
    
    # Read the list of file paths
    with open(file_list_path, 'r') as file_list:
        file_paths = [line.strip() for line in file_list.readlines()]
    
    # Sort file paths by size (optional, could help with distribution)
    file_paths.sort(key=get_file_size)
    
    # Merge files
    merge_files(target_dir, file_paths)

if __name__ == '__main__':
    main()

Run Code Interpreter

Running the following program: 

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import os

def get_file_size(file_path):
    """Get the size of a file."""
    return os.path.getsize(file_path)

def merge_files(target_dir, file_paths, num_files=16):
    """Merge files into a specified number of files with approximately equal size."""
    # Calculate total size of all files
    total_size = sum(get_file_size(path) for path in file_paths)
    
    # Target size per merged file
    target_size = total_size // num_files
    
    # Initialize variables
    current_file_size = 0
    current_file_index = 0
    merged_file = None
    
    for file_path in file_paths:
        # If there's no open file or the current file size exceeds the target, switch to a new file
        if not merged_file or current_file_size >= target_size:
            if merged_file:
                merged_file.close()
            merged_file_path = os.path.join(target_dir, f'merged_{current_file_index}')
            merged_file = open(merged_file_path, 'w')
            current_file_index += 1
            current_file_size = 0
        
        with open(file_path, 'r') as f:
            content = f.read()
            merged_file.write(content)
            current_file_size += len(content)
    
    # Close the last merged file
    if merged_file:
        merged_file.close()

def main():
    target_dir = '/tmp'
    file_list_path = '/tmp/files'
    
    # Read the list of file paths
    with open(file_list_path, 'r') as file_list:
        file_paths = [line.strip() for line in file_list.readlines()]
    
    # Sort file paths by size (optional, could help with distribution)
    file_paths.sort(key=get_file_size)
    
    # Merge files
    merge_files(target_dir, file_paths)

if __name__ == '__main__':
    main()
And got the output:

PyFunc

Traceback (most recent call last): File "/usr/src/app/check.py", line 20, in <module> print('final: ' + str(test())) ^^^^^^ File "/usr/src/app/check.py", line 6, in test sz.append(len(open("/tmp/merged_%d" % i).read())) ^^^^^^^^^^^^^^^^^^^^^^^^^^ FileNotFoundError: [Errno 2] No such file or directory: '/tmp/merged_15' Resulting in output: False

Docker Setup

I have setup the docker container to run the model evaluation.

Initial Query

I have a list of several thousand file paths in /tmp/files. Write a python script that merges the content int 16 files called /tmp/merged_%d for i in 0..15 where each is approximately the same size. "/tmp/files" is a list of file paths, one per line.

LLM Generation

Query

I have a list of several thousand file paths in /tmp/files. Write a python script that merges the content int 16 files called /tmp/merged_%d for i in 0..15 where each is approximately the same size. "/tmp/files" is a list of file paths, one per line.

Output

Below is a Python script that performs the task as specified. This script reads the list of file paths from `/tmp/files`, calculates the total size of all files to distribute them approximately evenly across the 16 output files, and then merges their content into those output files. 

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import os

def distribute_files_equally(file_paths, total_size, num_files=16):
    """
    Distribute files into buckets such that the total size is approximately
    equal across all buckets.
    """
    avg_size_per_file = total_size / num_files
    buckets = [[] for _ in range(num_files)]
    bucket_sizes = [0] * num_files
    for path in file_paths:
        # Find the bucket with the minimum size
        min_bucket_index = bucket_sizes.index(min(bucket_sizes))
        file_size = os.path.getsize(path)
        buckets[min_bucket_index].append(path)
        bucket_sizes[min_bucket_index] += file_size
    return buckets

def merge_files(file_paths, output_file):
    """
    Merge the content of the given file paths into a single output file.
    """
    with open(output_file, 'wb') as outfile:
        for path in file_paths:
            with open(path, 'rb') as infile:
                outfile.write(infile.read())

def main():
    input_file_list = '/tmp/files'
    output_prefix = '/tmp/merged_'
    num_output_files = 16

    # Read the list of file paths
    with open(input_file_list, 'r') as file:
        file_paths = file.read().splitlines()

    # Calculate the total size of all files
    total_size = sum(os.path.getsize(path) for path in file_paths)

    # Distribute the files approximately evenly by size
    distributed_files = distribute_files_equally(file_paths, total_size, num_output_files)

    # Merge the files into the specified number of output files
    for i, file_group in enumerate(distributed_files):
        output_file = f"{output_prefix}{i}"
        merge_files(file_group, output_file)
        print(f"Created {output_file} with {len(file_group)} files.")

if __name__ == "__main__":
    main()
This script starts by defining a function to distribute the files into 16 buckets such that each bucket has approximately the same total size. It then defines a function to merge the files in each bucket into a single output file. Finally, in the `main` function, it reads the list of file paths, calculates the total size, distributes the files, and merges them into the output files. Note: This script assumes that the file paths listed in `/tmp/files` are valid and accessible. It also opens files in binary mode (`'rb'` and `'wb'`) to ensure that any type of file (text, image, etc.) can be merged successfully without issues related to encoding or line endings.

Extract Code

I extracted the following code from that output: 

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import os

def distribute_files_equally(file_paths, total_size, num_files=16):
    """
    Distribute files into buckets such that the total size is approximately
    equal across all buckets.
    """
    avg_size_per_file = total_size / num_files
    buckets = [[] for _ in range(num_files)]
    bucket_sizes = [0] * num_files
    for path in file_paths:
        # Find the bucket with the minimum size
        min_bucket_index = bucket_sizes.index(min(bucket_sizes))
        file_size = os.path.getsize(path)
        buckets[min_bucket_index].append(path)
        bucket_sizes[min_bucket_index] += file_size
    return buckets

def merge_files(file_paths, output_file):
    """
    Merge the content of the given file paths into a single output file.
    """
    with open(output_file, 'wb') as outfile:
        for path in file_paths:
            with open(path, 'rb') as infile:
                outfile.write(infile.read())

def main():
    input_file_list = '/tmp/files'
    output_prefix = '/tmp/merged_'
    num_output_files = 16

    # Read the list of file paths
    with open(input_file_list, 'r') as file:
        file_paths = file.read().splitlines()

    # Calculate the total size of all files
    total_size = sum(os.path.getsize(path) for path in file_paths)

    # Distribute the files approximately evenly by size
    distributed_files = distribute_files_equally(file_paths, total_size, num_output_files)

    # Merge the files into the specified number of output files
    for i, file_group in enumerate(distributed_files):
        output_file = f"{output_prefix}{i}"
        merge_files(file_group, output_file)
        print(f"Created {output_file} with {len(file_group)} files.")

if __name__ == "__main__":
    main()

Run Code Interpreter

Running the following program: 

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import os

def distribute_files_equally(file_paths, total_size, num_files=16):
    """
    Distribute files into buckets such that the total size is approximately
    equal across all buckets.
    """
    avg_size_per_file = total_size / num_files
    buckets = [[] for _ in range(num_files)]
    bucket_sizes = [0] * num_files
    for path in file_paths:
        # Find the bucket with the minimum size
        min_bucket_index = bucket_sizes.index(min(bucket_sizes))
        file_size = os.path.getsize(path)
        buckets[min_bucket_index].append(path)
        bucket_sizes[min_bucket_index] += file_size
    return buckets

def merge_files(file_paths, output_file):
    """
    Merge the content of the given file paths into a single output file.
    """
    with open(output_file, 'wb') as outfile:
        for path in file_paths:
            with open(path, 'rb') as infile:
                outfile.write(infile.read())

def main():
    input_file_list = '/tmp/files'
    output_prefix = '/tmp/merged_'
    num_output_files = 16

    # Read the list of file paths
    with open(input_file_list, 'r') as file:
        file_paths = file.read().splitlines()

    # Calculate the total size of all files
    total_size = sum(os.path.getsize(path) for path in file_paths)

    # Distribute the files approximately evenly by size
    distributed_files = distribute_files_equally(file_paths, total_size, num_output_files)

    # Merge the files into the specified number of output files
    for i, file_group in enumerate(distributed_files):
        output_file = f"{output_prefix}{i}"
        merge_files(file_group, output_file)
        print(f"Created {output_file} with {len(file_group)} files.")

if __name__ == "__main__":
    main()
And got the output: Created /tmp/merged_0 with 19 files. Created /tmp/merged_1 with 56 files. Created /tmp/merged_2 with 43 files. Created /tmp/merged_3 with 46 files. Created /tmp/merged_4 with 15 files. Created /tmp/merged_5 with 82 files. Created /tmp/merged_6 with 76 files. Created /tmp/merged_7 with 73 files. Created /tmp/merged_8 with 75 files. Created /tmp/merged_9 with 69 files. Created /tmp/merged_10 with 74 files. Created /tmp/merged_11 with 78 files. Created /tmp/merged_12 with 72 files. Created /tmp/merged_13 with 78 files. Created /tmp/merged_14 with 70 files. Created /tmp/merged_15 with 74 files.

PyFunc

final: False Resulting in output: False

Docker Setup

I have setup the docker container to run the model evaluation.

Initial Query

I have a list of several thousand file paths in /tmp/files. Write a python script that merges the content int 16 files called /tmp/merged_%d for i in 0..15 where each is approximately the same size. "/tmp/files" is a list of file paths, one per line.

LLM Generation

Query

I have a list of several thousand file paths in /tmp/files. Write a python script that merges the content int 16 files called /tmp/merged_%d for i in 0..15 where each is approximately the same size. "/tmp/files" is a list of file paths, one per line.

Output

To merge the contents of several thousand files listed in `/tmp/files` into 16 files named `/tmp/merged_%d` for `i` in `0..15`, you can use the following Python script. This script reads the list of file paths, calculates the approximate number of files that should go into each merged file to balance their sizes, and then writes the contents into the respective merged files. 

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import os

def get_file_size(path):
    """Get the size of a file."""
    return os.path.getsize(path)

def read_file_paths(file_list_path):
    """Read file paths from a given list file."""
    with open(file_list_path, 'r') as file:
        paths = file.read().splitlines()
    return paths

def merge_files(file_paths, output_pattern, num_outputs):
    """Merge files into a specified number of output files approximately balancing their sizes."""
    # Calculate total size
    total_size = sum(get_file_size(path) for path in file_paths)
    
    # Calculate approximate size per output file
    size_per_output = total_size // num_outputs
    
    # Initialize variables for merging process
    current_output_index = 0
    current_output_size = 0
    output_files = [open(output_pattern % i, 'wb') for i in range(num_outputs)]
    
    for path in file_paths:
        # If the current output file exceeds the approximate size, move to the next one
        if current_output_size > size_per_output and current_output_index < num_outputs - 1:
            current_output_index += 1
            current_output_size = 0
        
        # Read and write the current file's content
        with open(path, 'rb') as current_file:
            content = current_file.read()
            output_files[current_output_index].write(content)
            current_output_size += len(content)
    
    # Close all output files
    for file in output_files:
        file.close()

# Parameters
file_list_path = '/tmp/files'
output_pattern = '/tmp/merged_%d'
num_outputs = 16

# Execution
file_paths = read_file_paths(file_list_path)
merge_files(file_paths, output_pattern, num_outputs)
This script does the following: 1. Reads the list of file paths from `/tmp/files`. 2. Calculates the total size of all files to be merged and divides it by 16 to get an approximate size per output file for even distribution. 3. Iterates through each file, merging its content into one of the 16 output files. It switches to the next output file once the current output file's size exceeds the calculated approximate size, ensuring an even distribution of content. 4. It writes the contents in binary mode (`'rb'` and `'wb'`) to handle all types of files without issues related to text encoding. Make sure you have the necessary permissions to read the listed files and write to the destination directory.

Extract Code

I extracted the following code from that output: 

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import os

def get_file_size(path):
    """Get the size of a file."""
    return os.path.getsize(path)

def read_file_paths(file_list_path):
    """Read file paths from a given list file."""
    with open(file_list_path, 'r') as file:
        paths = file.read().splitlines()
    return paths

def merge_files(file_paths, output_pattern, num_outputs):
    """Merge files into a specified number of output files approximately balancing their sizes."""
    # Calculate total size
    total_size = sum(get_file_size(path) for path in file_paths)
    
    # Calculate approximate size per output file
    size_per_output = total_size // num_outputs
    
    # Initialize variables for merging process
    current_output_index = 0
    current_output_size = 0
    output_files = [open(output_pattern % i, 'wb') for i in range(num_outputs)]
    
    for path in file_paths:
        # If the current output file exceeds the approximate size, move to the next one
        if current_output_size > size_per_output and current_output_index < num_outputs - 1:
            current_output_index += 1
            current_output_size = 0
        
        # Read and write the current file's content
        with open(path, 'rb') as current_file:
            content = current_file.read()
            output_files[current_output_index].write(content)
            current_output_size += len(content)
    
    # Close all output files
    for file in output_files:
        file.close()

# Parameters
file_list_path = '/tmp/files'
output_pattern = '/tmp/merged_%d'
num_outputs = 16

# Execution
file_paths = read_file_paths(file_list_path)
merge_files(file_paths, output_pattern, num_outputs)

Run Code Interpreter

Running the following program: 

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import os

def get_file_size(path):
    """Get the size of a file."""
    return os.path.getsize(path)

def read_file_paths(file_list_path):
    """Read file paths from a given list file."""
    with open(file_list_path, 'r') as file:
        paths = file.read().splitlines()
    return paths

def merge_files(file_paths, output_pattern, num_outputs):
    """Merge files into a specified number of output files approximately balancing their sizes."""
    # Calculate total size
    total_size = sum(get_file_size(path) for path in file_paths)
    
    # Calculate approximate size per output file
    size_per_output = total_size // num_outputs
    
    # Initialize variables for merging process
    current_output_index = 0
    current_output_size = 0
    output_files = [open(output_pattern % i, 'wb') for i in range(num_outputs)]
    
    for path in file_paths:
        # If the current output file exceeds the approximate size, move to the next one
        if current_output_size > size_per_output and current_output_index < num_outputs - 1:
            current_output_index += 1
            current_output_size = 0
        
        # Read and write the current file's content
        with open(path, 'rb') as current_file:
            content = current_file.read()
            output_files[current_output_index].write(content)
            current_output_size += len(content)
    
    # Close all output files
    for file in output_files:
        file.close()

# Parameters
file_list_path = '/tmp/files'
output_pattern = '/tmp/merged_%d'
num_outputs = 16

# Execution
file_paths = read_file_paths(file_list_path)
merge_files(file_paths, output_pattern, num_outputs)
And got the output:

PyFunc

final: False Resulting in output: False

Docker Setup

I have setup the docker container to run the model evaluation.

Initial Query

I have a list of several thousand file paths in /tmp/files. Write a python script that merges the content int 16 files called /tmp/merged_%d for i in 0..15 where each is approximately the same size. "/tmp/files" is a list of file paths, one per line.

LLM Generation

Query

I have a list of several thousand file paths in /tmp/files. Write a python script that merges the content int 16 files called /tmp/merged_%d for i in 0..15 where each is approximately the same size. "/tmp/files" is a list of file paths, one per line.

Output

To accomplish this task, you can follow these steps in your Python script: 1. Read the list of file paths from `/tmp/files`. 2. Calculate the total size of all files to distribute them evenly. 3. Open 16 output files for writing. 4. Iterate through each file path, read its content, and write it to one of the output files in a round-robin fashion or based on size constraints. 5. Close all files. Here's a basic implementation to get you started. This script aims to balance the output files by size as evenly as possible. Note that this approach assumes that individual file sizes are not significantly larger than the total size divided by 16, as that could lead to less optimal distribution. 

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import os

def get_file_size(path):
    """Returns the size of the file at the given path."""
    return os.path.getsize(path)

def distribute_files_evenly(file_paths, total_size, num_files=16):
    """Distributes file paths into buckets (num_files) based on size."""
    # Calculate the target size per file
    target_size_per_file = total_size / num_files
    
    # Initialize data structures to hold file distribution
    distribution = [[] for _ in range(num_files)]
    current_sizes = [0] * num_files
    
    # Distribute files
    for path in file_paths:
        # Find the file with the minimum current size
        index = current_sizes.index(min(current_sizes))
        distribution[index].append(path)
        current_sizes[index] += get_file_size(path)
    
    return distribution

def merge_files(file_paths, output_path_template="/tmp/merged_%d"):
    """Merges files from file_paths into multiple files."""
    # Calculate total size of all files
    total_size = sum(get_file_size(path) for path in file_paths)
    
    # Distribute files into 16 buckets approximately evenly by size
    distribution = distribute_files_evenly(file_paths, total_size)
    
    # Write files from each bucket into a corresponding output file
    for i, paths in enumerate(distribution):
        with open(output_path_template % i, 'wb') as output_file:
            for path in paths:
                with open(path, 'rb') as input_file:
                    output_file.write(input_file.read())

def main():
    file_list_path = "/tmp/files"
    
    # Read file paths from /tmp/files
    with open(file_list_path, 'r') as file:
        file_paths = file.read().splitlines()
    
    # Merge files into 16 approximately equal-sized files
    merge_files(file_paths)

if __name__ == "__main__":
    main()
This script does the following: - Reads the list of file paths from `/tmp/files`. - Calculates the total size of all files to help with even distribution. - Distributes files into 16 buckets, aiming to balance the total size in each bucket. - Writes the content of files from each bucket into a corresponding merged file. This approach is a simple way to distribute files by size. However, it's worth noting that there are more sophisticated algorithms for balancing if you have specific requirements or if the files vary greatly in size.

Extract Code

I extracted the following code from that output: 

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import os

def get_file_size(path):
    """Returns the size of the file at the given path."""
    return os.path.getsize(path)

def distribute_files_evenly(file_paths, total_size, num_files=16):
    """Distributes file paths into buckets (num_files) based on size."""
    # Calculate the target size per file
    target_size_per_file = total_size / num_files
    
    # Initialize data structures to hold file distribution
    distribution = [[] for _ in range(num_files)]
    current_sizes = [0] * num_files
    
    # Distribute files
    for path in file_paths:
        # Find the file with the minimum current size
        index = current_sizes.index(min(current_sizes))
        distribution[index].append(path)
        current_sizes[index] += get_file_size(path)
    
    return distribution

def merge_files(file_paths, output_path_template="/tmp/merged_%d"):
    """Merges files from file_paths into multiple files."""
    # Calculate total size of all files
    total_size = sum(get_file_size(path) for path in file_paths)
    
    # Distribute files into 16 buckets approximately evenly by size
    distribution = distribute_files_evenly(file_paths, total_size)
    
    # Write files from each bucket into a corresponding output file
    for i, paths in enumerate(distribution):
        with open(output_path_template % i, 'wb') as output_file:
            for path in paths:
                with open(path, 'rb') as input_file:
                    output_file.write(input_file.read())

def main():
    file_list_path = "/tmp/files"
    
    # Read file paths from /tmp/files
    with open(file_list_path, 'r') as file:
        file_paths = file.read().splitlines()
    
    # Merge files into 16 approximately equal-sized files
    merge_files(file_paths)

if __name__ == "__main__":
    main()

Run Code Interpreter

Running the following program: 

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import os

def get_file_size(path):
    """Returns the size of the file at the given path."""
    return os.path.getsize(path)

def distribute_files_evenly(file_paths, total_size, num_files=16):
    """Distributes file paths into buckets (num_files) based on size."""
    # Calculate the target size per file
    target_size_per_file = total_size / num_files
    
    # Initialize data structures to hold file distribution
    distribution = [[] for _ in range(num_files)]
    current_sizes = [0] * num_files
    
    # Distribute files
    for path in file_paths:
        # Find the file with the minimum current size
        index = current_sizes.index(min(current_sizes))
        distribution[index].append(path)
        current_sizes[index] += get_file_size(path)
    
    return distribution

def merge_files(file_paths, output_path_template="/tmp/merged_%d"):
    """Merges files from file_paths into multiple files."""
    # Calculate total size of all files
    total_size = sum(get_file_size(path) for path in file_paths)
    
    # Distribute files into 16 buckets approximately evenly by size
    distribution = distribute_files_evenly(file_paths, total_size)
    
    # Write files from each bucket into a corresponding output file
    for i, paths in enumerate(distribution):
        with open(output_path_template % i, 'wb') as output_file:
            for path in paths:
                with open(path, 'rb') as input_file:
                    output_file.write(input_file.read())

def main():
    file_list_path = "/tmp/files"
    
    # Read file paths from /tmp/files
    with open(file_list_path, 'r') as file:
        file_paths = file.read().splitlines()
    
    # Merge files into 16 approximately equal-sized files
    merge_files(file_paths)

if __name__ == "__main__":
    main()
And got the output:

PyFunc

final: False Resulting in output: False